テスト

Testing output of the coding.

## Loading the packages and setting adjustment
suppressMessages(source('function/libs.R'))

1. DT, 2. DT, 3. DT: #DT

## Read the datasets
## Refer to **Testing efficiency of coding.Rmd** at chunk `get-data-summary-table-2.1`
years <- seq(2011, 2015)

## Here I take the majority leagues setting profile which are "league-10-12"
## fMYPriceB = Back with vigorish price; fMYPriceL = Lay with vigorish price
## Here we term as Fair Odds
lProfile <- c(AH=0.10,OU=0.12)

mbase <- readfirmDatasets(years=years) %>% arrfirmDatasets(., lProfile=lProfile)

## In order to analyse the AHOU, here I need to filter out all soccer matches other than AHOU. (For example : Corners, Total League Goals etc.)
## the stakes amount display as $1 = $10,000
#'@ mbase$datasets[!(mbase$datasets$Home %in% mbase$corners)|!(mbase$datasets$Away %in% mbase$corners),]

dat <- mbase$data
dat %>% datatable(., caption="Table 2.1.1 : Firm A Staking Data",
    extensions = list("ColReorder"=NULL,
                      "ColVis"=NULL,
                      "TableTools"=NULL #, "FixedColumns"=list(leftColumns=2)
                      ), 
    options = list(autoWidth=TRUE,
                   oColReorder=list(realtime=TRUE), #oColVis=list(exclude=c(0, 1), activate='mouseover'),
                   oTableTools = list(
                   sSwfPath = "//cdnjs.cloudflare.com/ajax/libs/datatables-tabletools/2.1.5/swf/copy_csv_xls.swf",
                   aButtons = list("copy", "print",
                                   list(sExtends="collection",
                                        sButtonText="Save",
                                        aButtons=c("csv","xls")))),
               dom='CRTrilftp', scrollX=TRUE, scrollCollapse=TRUE,
               colVis=list(exclude=c(0), activate='mouseover')))

rm(years, readfirmDatasets, arrfirmDatasets)
rm(mbase) ## We need to scrap the livescore data based on the raw data mbase without filter, but this is not the point in this research paper.

Please refer to Natural Language Analysis to see the firm A staking sample dataset.

summary(lm(Return~pHKRange, data=dat))

## 
## Call:
## lm(formula = Return ~ pHKRange, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -628382  -379397  -173601   121865 29316045 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)
## (Intercept)         620000     795518   0.779    0.436
## pHKRange(0.2,0.3]  -418362     974307  -0.429    0.668
## pHKRange(0.3,0.4]  -404820     810116  -0.500    0.617
## pHKRange(0.4,0.5]  -387706     797154  -0.486    0.627
## pHKRange(0.5,0.6]  -338596     795835  -0.425    0.671
## pHKRange(0.6,0.7]  -324606     795605  -0.408    0.683
## pHKRange(0.7,0.8]  -240603     795569  -0.302    0.762
## pHKRange(0.8,0.9]   -16045     795566  -0.020    0.984
## pHKRange(0.9,1]       8382     795564   0.011    0.992
## pHKRange(1,1.1]     -88870     795573  -0.112    0.911
## pHKRange(1.1,1.2]  -299335     795598  -0.376    0.707
## pHKRange(1.2,1.3]  -407034     795648  -0.512    0.609
## pHKRange(1.3,1.4]  -484208     795808  -0.608    0.543
## pHKRange(1.4,1.5]  -485097     796191  -0.609    0.542
## pHKRange(1.5,1.6]  -521829     797167  -0.655    0.513
## pHKRange(1.6,1.7]  -513714     799567  -0.642    0.521
## pHKRange(1.7,1.8]  -233847     805653  -0.290    0.772
## pHKRange(1.8,1.9]  -503617     811923  -0.620    0.535
## pHKRange(1.9,2]    -402615     825548  -0.488    0.626
## pHKRange(2,2.1]    -620000    1125033  -0.551    0.582
## pHKRange(2.1,2.2]  -589500     889417  -0.663    0.507
## pHKRange(2.2,2.3]  -174400     871447  -0.200    0.841
## pHKRange(2.3,2.4]  -245000     974307  -0.251    0.801
## pHKRange(2.4,2.5]  -560000     850445  -0.658    0.510
## pHKRange(2.5,2.6]  -490000     974307  -0.503    0.615
## pHKRange(2.6,2.7]   513050    1125033   0.456    0.648
## pHKRange(2.7,2.8]   685000    1125033   0.609    0.543
## pHKRange(2.8,2.9]  -620000    1125033  -0.551    0.582
## pHKRange(2.9,3]    -520000    1125033  -0.462    0.644
## pHKRange(3.3,3.4]  -620000    1125033  -0.551    0.582
## pHKRange(3.7,3.8]  -610000    1125033  -0.542    0.588
## pHKRange(3.8,3.9]  -620000    1125033  -0.551    0.582
## 
## Residual standard error: 795500 on 48712 degrees of freedom
## Multiple R-squared:  0.03801,    Adjusted R-squared:  0.03739 
## F-statistic: 62.08 on 31 and 48712 DF,  p-value: < 2.2e-16

DT

Table summary

summary(lm(Return~HCap, data=dat))

## 
## Call:
## lm(formula = Return ~ HCap, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -617075  -419790  -247974   132566 29509604 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   485552       4666  104.06   <2e-16 ***
## HCap          -37578       2669  -14.08   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 809200 on 48742 degrees of freedom
## Multiple R-squared:  0.00405,    Adjusted R-squared:  0.00403 
## F-statistic: 198.2 on 1 and 48742 DF,  p-value: < 2.2e-16

graph 3.4.1b linear model

summary(lm(Return~pHKRange, data=dat))

## 
## Call:
## lm(formula = Return ~ pHKRange, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -628382  -379397  -173601   121865 29316045 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)
## (Intercept)         620000     795518   0.779    0.436
## pHKRange(0.2,0.3]  -418362     974307  -0.429    0.668
## pHKRange(0.3,0.4]  -404820     810116  -0.500    0.617
## pHKRange(0.4,0.5]  -387706     797154  -0.486    0.627
## pHKRange(0.5,0.6]  -338596     795835  -0.425    0.671
## pHKRange(0.6,0.7]  -324606     795605  -0.408    0.683
## pHKRange(0.7,0.8]  -240603     795569  -0.302    0.762
## pHKRange(0.8,0.9]   -16045     795566  -0.020    0.984
## pHKRange(0.9,1]       8382     795564   0.011    0.992
## pHKRange(1,1.1]     -88870     795573  -0.112    0.911
## pHKRange(1.1,1.2]  -299335     795598  -0.376    0.707
## pHKRange(1.2,1.3]  -407034     795648  -0.512    0.609
## pHKRange(1.3,1.4]  -484208     795808  -0.608    0.543
## pHKRange(1.4,1.5]  -485097     796191  -0.609    0.542
## pHKRange(1.5,1.6]  -521829     797167  -0.655    0.513
## pHKRange(1.6,1.7]  -513714     799567  -0.642    0.521
## pHKRange(1.7,1.8]  -233847     805653  -0.290    0.772
## pHKRange(1.8,1.9]  -503617     811923  -0.620    0.535
## pHKRange(1.9,2]    -402615     825548  -0.488    0.626
## pHKRange(2,2.1]    -620000    1125033  -0.551    0.582
## pHKRange(2.1,2.2]  -589500     889417  -0.663    0.507
## pHKRange(2.2,2.3]  -174400     871447  -0.200    0.841
## pHKRange(2.3,2.4]  -245000     974307  -0.251    0.801
## pHKRange(2.4,2.5]  -560000     850445  -0.658    0.510
## pHKRange(2.5,2.6]  -490000     974307  -0.503    0.615
## pHKRange(2.6,2.7]   513050    1125033   0.456    0.648
## pHKRange(2.7,2.8]   685000    1125033   0.609    0.543
## pHKRange(2.8,2.9]  -620000    1125033  -0.551    0.582
## pHKRange(2.9,3]    -520000    1125033  -0.462    0.644
## pHKRange(3.3,3.4]  -620000    1125033  -0.551    0.582
## pHKRange(3.7,3.8]  -610000    1125033  -0.542    0.588
## pHKRange(3.8,3.9]  -620000    1125033  -0.551    0.582
## 
## Residual standard error: 795500 on 48712 degrees of freedom
## Multiple R-squared:  0.03801,    Adjusted R-squared:  0.03739 
## F-statistic: 62.08 on 31 and 48712 DF,  p-value: < 2.2e-16

test

summary(lm(Return~HCap+HKPrice, data=dat))

## 
## Call:
## lm(formula = Return ~ HCap + HKPrice, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -676314  -418990  -246621   129505 29498236 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   655572      17078   38.39   <2e-16 ***
## HCap          -39526       2673  -14.79   <2e-16 ***
## HKPrice      -177882      17189  -10.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 808300 on 48741 degrees of freedom
## Multiple R-squared:  0.006234,   Adjusted R-squared:  0.006193 
## F-statistic: 152.9 on 2 and 48741 DF,  p-value: < 2.2e-16

summary(lm(Return~ipRange, data=dat))

## 
## Call:
## lm(formula = Return ~ ipRange, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1165445  -425993  -253903   134356 29455497 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     415080.1    12757.9  32.535  < 2e-16 ***
## ipRange(10,15]   46779.3    23157.6   2.020 0.043385 *  
## ipRange(15,20]   31877.8    23311.5   1.367 0.171483    
## ipRange(20,25]   13349.5    23208.4   0.575 0.565158    
## ipRange(25,30]  -25036.9    23062.2  -1.086 0.277649    
## ipRange(30,35]    1334.9    23176.0   0.058 0.954068    
## ipRange(35,40]   26019.7    24165.7   1.077 0.281611    
## ipRange(40,45]   19519.5    23514.5   0.830 0.406482    
## ipRange(45,50]   23193.5    24812.7   0.935 0.349925    
## ipRange(5,10]    10913.1    19661.9   0.555 0.578871    
## ipRange(50,55]    1182.9    23035.2   0.051 0.959046    
## ipRange(55,60]   -9864.8    23941.2  -0.412 0.680311    
## ipRange(60,65]    2232.5    26892.2   0.083 0.933840    
## ipRange(65,70]    4606.1    29404.9   0.157 0.875527    
## ipRange(70,75]   -4889.1    31790.6  -0.154 0.877777    
## ipRange(75,80]    -522.8    40882.8  -0.013 0.989797    
## ipRange(80,85]   45026.3    72457.2   0.621 0.534327    
## ipRange(85,90]  152711.5   270334.2   0.565 0.572145    
## ipRangeET       750364.9   104504.2   7.180 7.06e-13 ***
## ipRangeFT      -142010.1   209555.3  -0.678 0.497982    
## ipRangeHT       123497.5    25733.2   4.799 1.60e-06 ***
## ipRangeNo        49423.3    13978.6   3.536 0.000407 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 810100 on 48722 degrees of freedom
## Multiple R-squared:  0.002215,   Adjusted R-squared:  0.001785 
## F-statistic: 5.151 on 21 and 48722 DF,  p-value: 1.045e-13

summary(lm(Return~CurScore+ipHCap, data=dat))

## 
## Call:
## lm(formula = Return ~ CurScore + ipHCap, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2102677  -412898  -243608   128388 29422983 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   404130       7444  54.291  < 2e-16 ***
## CurScore0-1    33218      16770   1.981 0.047624 *  
## CurScore0-2    19673      34853   0.564 0.572443    
## CurScore0-3    98248      93919   1.046 0.295528    
## CurScore0-4   104458     226193   0.462 0.644221    
## CurScore0-5  -120002     452206  -0.265 0.790726    
## CurScore1-0    23202      15729   1.475 0.140191    
## CurScore1-1    49854      24052   2.073 0.038205 *  
## CurScore1-2    35157      38029   0.924 0.355243    
## CurScore1-3    -1681     102224  -0.016 0.986881    
## CurScore1-4   -32695     217316  -0.150 0.880412    
## CurScore2-0    31990      24711   1.295 0.195479    
## CurScore2-1    71126      44138   1.611 0.107091    
## CurScore2-2    77528      73401   1.056 0.290873    
## CurScore2-3   129370     119651   1.081 0.279602    
## CurScore2-4  -145296     452183  -0.321 0.747969    
## CurScore3-0    11844      62355   0.190 0.849348    
## CurScore3-1    74653      85770   0.870 0.384093    
## CurScore3-2    27766     190073   0.146 0.883857    
## CurScore3-3   227428     236226   0.963 0.335677    
## CurScore3-4  2276046     553767   4.110 3.96e-05 ***
## CurScore4-0     1893     236241   0.008 0.993607    
## CurScore4-1    31050     209421   0.148 0.882133    
## CurScore4-2   -65668     296074  -0.222 0.824473    
## CurScore4-3   439105     783116   0.561 0.574995    
## CurScore5-0   -91761     247837  -0.370 0.711199    
## CurScore5-1  -363012     783119  -0.464 0.642976    
## CurScore5-2   -37820     553813  -0.068 0.945555    
## CurScore5-3   187339     783134   0.239 0.810938    
## CurScore8-3  -212245     783300  -0.271 0.786421    
## CurScoreNo     38063       9958   3.822 0.000132 ***
## ipHCap        -27412       2462 -11.135  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 783100 on 35367 degrees of freedom
##   (13345 observations deleted due to missingness)
## Multiple R-squared:  0.004816,   Adjusted R-squared:  0.003944 
## F-statistic: 5.521 on 31 and 35367 DF,  p-value: < 2.2e-16

=======

Table summary

summary(lm(Return~HCap, data=dat))

## 
## Call:
## lm(formula = Return ~ HCap, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -617075  -419790  -247974   132566 29509604 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   485552       4666  104.06   <2e-16 ***
## HCap          -37578       2669  -14.08   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 809200 on 48742 degrees of freedom
## Multiple R-squared:  0.00405,    Adjusted R-squared:  0.00403 
## F-statistic: 198.2 on 1 and 48742 DF,  p-value: < 2.2e-16

graph 3.4.1b linear model

summary(lm(Return~pHKRange, data=dat))

## 
## Call:
## lm(formula = Return ~ pHKRange, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -628382  -379397  -173601   121865 29316045 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)
## (Intercept)         620000     795518   0.779    0.436
## pHKRange(0.2,0.3]  -418362     974307  -0.429    0.668
## pHKRange(0.3,0.4]  -404820     810116  -0.500    0.617
## pHKRange(0.4,0.5]  -387706     797154  -0.486    0.627
## pHKRange(0.5,0.6]  -338596     795835  -0.425    0.671
## pHKRange(0.6,0.7]  -324606     795605  -0.408    0.683
## pHKRange(0.7,0.8]  -240603     795569  -0.302    0.762
## pHKRange(0.8,0.9]   -16045     795566  -0.020    0.984
## pHKRange(0.9,1]       8382     795564   0.011    0.992
## pHKRange(1,1.1]     -88870     795573  -0.112    0.911
## pHKRange(1.1,1.2]  -299335     795598  -0.376    0.707
## pHKRange(1.2,1.3]  -407034     795648  -0.512    0.609
## pHKRange(1.3,1.4]  -484208     795808  -0.608    0.543
## pHKRange(1.4,1.5]  -485097     796191  -0.609    0.542
## pHKRange(1.5,1.6]  -521829     797167  -0.655    0.513
## pHKRange(1.6,1.7]  -513714     799567  -0.642    0.521
## pHKRange(1.7,1.8]  -233847     805653  -0.290    0.772
## pHKRange(1.8,1.9]  -503617     811923  -0.620    0.535
## pHKRange(1.9,2]    -402615     825548  -0.488    0.626
## pHKRange(2,2.1]    -620000    1125033  -0.551    0.582
## pHKRange(2.1,2.2]  -589500     889417  -0.663    0.507
## pHKRange(2.2,2.3]  -174400     871447  -0.200    0.841
## pHKRange(2.3,2.4]  -245000     974307  -0.251    0.801
## pHKRange(2.4,2.5]  -560000     850445  -0.658    0.510
## pHKRange(2.5,2.6]  -490000     974307  -0.503    0.615
## pHKRange(2.6,2.7]   513050    1125033   0.456    0.648
## pHKRange(2.7,2.8]   685000    1125033   0.609    0.543
## pHKRange(2.8,2.9]  -620000    1125033  -0.551    0.582
## pHKRange(2.9,3]    -520000    1125033  -0.462    0.644
## pHKRange(3.3,3.4]  -620000    1125033  -0.551    0.582
## pHKRange(3.7,3.8]  -610000    1125033  -0.542    0.588
## pHKRange(3.8,3.9]  -620000    1125033  -0.551    0.582
## 
## Residual standard error: 795500 on 48712 degrees of freedom
## Multiple R-squared:  0.03801,    Adjusted R-squared:  0.03739 
## F-statistic: 62.08 on 31 and 48712 DF,  p-value: < 2.2e-16

summary(lm(Return~HCap+HKPrice, data=dat))

## 
## Call:
## lm(formula = Return ~ HCap + HKPrice, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
##  -676314  -418990  -246621   129505 29498236 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   655572      17078   38.39   <2e-16 ***
## HCap          -39526       2673  -14.79   <2e-16 ***
## HKPrice      -177882      17189  -10.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 808300 on 48741 degrees of freedom
## Multiple R-squared:  0.006234,   Adjusted R-squared:  0.006193 
## F-statistic: 152.9 on 2 and 48741 DF,  p-value: < 2.2e-16

summary(lm(Return~ipRange, data=dat))

## 
## Call:
## lm(formula = Return ~ ipRange, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1165445  -425993  -253903   134356 29455497 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     415080.1    12757.9  32.535  < 2e-16 ***
## ipRange(10,15]   46779.3    23157.6   2.020 0.043385 *  
## ipRange(15,20]   31877.8    23311.5   1.367 0.171483    
## ipRange(20,25]   13349.5    23208.4   0.575 0.565158    
## ipRange(25,30]  -25036.9    23062.2  -1.086 0.277649    
## ipRange(30,35]    1334.9    23176.0   0.058 0.954068    
## ipRange(35,40]   26019.7    24165.7   1.077 0.281611    
## ipRange(40,45]   19519.5    23514.5   0.830 0.406482    
## ipRange(45,50]   23193.5    24812.7   0.935 0.349925    
## ipRange(5,10]    10913.1    19661.9   0.555 0.578871    
## ipRange(50,55]    1182.9    23035.2   0.051 0.959046    
## ipRange(55,60]   -9864.8    23941.2  -0.412 0.680311    
## ipRange(60,65]    2232.5    26892.2   0.083 0.933840    
## ipRange(65,70]    4606.1    29404.9   0.157 0.875527    
## ipRange(70,75]   -4889.1    31790.6  -0.154 0.877777    
## ipRange(75,80]    -522.8    40882.8  -0.013 0.989797    
## ipRange(80,85]   45026.3    72457.2   0.621 0.534327    
## ipRange(85,90]  152711.5   270334.2   0.565 0.572145    
## ipRangeET       750364.9   104504.2   7.180 7.06e-13 ***
## ipRangeFT      -142010.1   209555.3  -0.678 0.497982    
## ipRangeHT       123497.5    25733.2   4.799 1.60e-06 ***
## ipRangeNo        49423.3    13978.6   3.536 0.000407 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 810100 on 48722 degrees of freedom
## Multiple R-squared:  0.002215,   Adjusted R-squared:  0.001785 
## F-statistic: 5.151 on 21 and 48722 DF,  p-value: 1.045e-13

summary(lm(Return~CurScore+ipHCap, data=dat))

## 
## Call:
## lm(formula = Return ~ CurScore + ipHCap, data = dat)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2102677  -412898  -243608   128388 29422983 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   404130       7444  54.291  < 2e-16 ***
## CurScore0-1    33218      16770   1.981 0.047624 *  
## CurScore0-2    19673      34853   0.564 0.572443    
## CurScore0-3    98248      93919   1.046 0.295528    
## CurScore0-4   104458     226193   0.462 0.644221    
## CurScore0-5  -120002     452206  -0.265 0.790726    
## CurScore1-0    23202      15729   1.475 0.140191    
## CurScore1-1    49854      24052   2.073 0.038205 *  
## CurScore1-2    35157      38029   0.924 0.355243    
## CurScore1-3    -1681     102224  -0.016 0.986881    
## CurScore1-4   -32695     217316  -0.150 0.880412    
## CurScore2-0    31990      24711   1.295 0.195479    
## CurScore2-1    71126      44138   1.611 0.107091    
## CurScore2-2    77528      73401   1.056 0.290873    
## CurScore2-3   129370     119651   1.081 0.279602    
## CurScore2-4  -145296     452183  -0.321 0.747969    
## CurScore3-0    11844      62355   0.190 0.849348    
## CurScore3-1    74653      85770   0.870 0.384093    
## CurScore3-2    27766     190073   0.146 0.883857    
## CurScore3-3   227428     236226   0.963 0.335677    
## CurScore3-4  2276046     553767   4.110 3.96e-05 ***
## CurScore4-0     1893     236241   0.008 0.993607    
## CurScore4-1    31050     209421   0.148 0.882133    
## CurScore4-2   -65668     296074  -0.222 0.824473    
## CurScore4-3   439105     783116   0.561 0.574995    
## CurScore5-0   -91761     247837  -0.370 0.711199    
## CurScore5-1  -363012     783119  -0.464 0.642976    
## CurScore5-2   -37820     553813  -0.068 0.945555    
## CurScore5-3   187339     783134   0.239 0.810938    
## CurScore8-3  -212245     783300  -0.271 0.786421    
## CurScoreNo     38063       9958   3.822 0.000132 ***
## ipHCap        -27412       2462 -11.135  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 783100 on 35367 degrees of freedom
##   (13345 observations deleted due to missingness)
## Multiple R-squared:  0.004816,   Adjusted R-squared:  0.003944 
## F-statistic: 5.521 on 31 and 35367 DF,  p-value: < 2.2e-16

graph 3.4.1c linear model

## Set options back to original options
options(op)

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